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shiny_Init.R
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shiny_Init.R
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suppressPackageStartupMessages(library(tm))
suppressPackageStartupMessages(library(topicmodels))
suppressPackageStartupMessages(library(proxy))
suppressPackageStartupMessages(library(parallel))
suppressPackageStartupMessages(library(slam))
suppressPackageStartupMessages(library(docopt))
suppressPackageStartupMessages(library(reshape2))
doc<-"This script takes the topic models, corpus and metadata and creates the files/data necessary for deployment to the shiny app.
Usage: shiny_Init.R --corpus=<corpus> --shiny=<shiny>
Options:
--corpus=<corpus> Directory where corpus and models are stored
--shiny=<shiny> Directory where shiny app is located [default:current directory]
-h --help This helpful message"
my_opts<-docopt(doc)
##Run this when working interactively
#my_opts<-list(corpus="data/Pubmed_2016-04-11", shiny="shiny/data")
dist2Table<-function(x){
library(reshape2)
t<-melt(x[1:dim(x)[1],1:dim(x)[2]], varnames=c("source","target"))
t[t$target>t$source,]
}
print(my_opts) ##This is for testing purposes
if(is.null(my_opts$shiny)){
my_opts$shiny<-getwd()
}
my_opts$shiny<-gsub("/$", "", my_opts$shiny)
my_opts$corpus<-gsub("/$","",my_opts$corpus)
ICs<-c("NCI","NICHD","NIMHD","NCCIH",
"NEI","NIDID","NINDS","NCATS",
"NHLBI","NIDCR","NINR","NHGRI",
"NIDDK","NLM","NIAID","NIEHS",
"CIT","NIAMS","NIGMS","CSR",
"FDA","NCTR","NIBIB","NIMH",
"FIC","NIH", "HHS","EPA","HHS",
"PHS","RFA","FOA")
tlc<-list(AHRG="HS",
NIH=c("AA","AG","AI","AR","AT","CA","CL","DA","DC",
"DE","DK","EB","ES","EY","GM","HD","HG","HL",
"LM","MD","MH","NR","NS","RM","RR","TR","TW",
"OD","WH"),
CDC=c("CC","CD","CE","CH","CI","CK","DD","DP","EH","EP","GD","GH",
"HK","HM","HY","IP","LS","LS","MN","ND","OE","OH","OW","PH",
"PR","PS","SE","SH","SO","TP","TS","WC"),
FDA=c("FD","BI","BJ","BK","BL","BM","BN","BO","BP","BQ","BR","BS",
"BT","BU"),
SAMHA=c("SU","OA","SM","SP","SU","TI"),
VA=c("BX","CU","CX","HX","RD","RX"))
activityCodes<-"C06,D43,D71,DP1,DP2,DP3,DP4,DP5,DP7,E11,F05,F30,F31,F32,F33,F37,F38,F99,FI2,G07,G08,G11,G12,G13,G20,G94,H13,H25,H50,H57,H62,H64,H75,H79,HD4,I01,IK3,K00,K01,K02,K05,K06,K07,K08,K12,K14,K18,K21,K22,K23,K24,K25,K26,K30,K43,K76,K99,KD1,KL1,KL2,KM1,L30,L32,L40,L50,L60,M01,OT1,OT2,P01,P20,P2C,P30,P40,P41,P42,P50,P51,P60,PL1,PM1,PN1,PN2,R00,R01,R03,R13,R15,R18,R21,R24,R25,R28,R30,R33,R34,R35,R36,R37,R41,R42,R43,R44,R49,R50,R55,R56,R61,R90,RC1,RC2,RC3,RC4,RF1,RL1,RL2,RL5,RL9,RM1,RS1,S06,S07,S10,S11,S21,S22,SB1,SC1,SC2,SC3,SI2,T01,T02,T09,T14,T15,T32,T34,T35,T37,T42,T90,TL1,TL4,TU2,U01,U09,U10,U11,U13,U17,U18,U19,U1A,U1B,U1Q,U1V,U21,U22,U23,U24,U27,U2C,U2G,U2R,U30,U32,U34,U36,U38,U41,U42,U43,U44,U45,U47,U48,U49,U50,U51,U52,U53,U54,U55,U56,U57,U58,U59,U60,U61,U62,U65,U66,U75,U79,U81,U82,U83,U84,U90,UA1,UA5,UB1,UC1,UC2,UC3,UC4,UC6,UC7,UD1,UE1,UE2,UF1,UF2,UG1,UG3,UG4,UH1,UH2,UH3,UH4,UL1,UM1,UM2,UP5,UR6,UR8,US3,US4,UT1,UT2,VF1,VF1,X01,X02,X98,X99"
activityCodes<-c(unlist(strsplit(activityCodes,",")),"Z01","ZIA")
corpus<-Corpus(DirSource(paste0(my_opts$corpus,"/Corpus/")),
readerControl = list(language="english"))
###Need to create shiny data directory structure
dir.create(paste0(my_opts$shiny,"/data"))
dir.create(paste0(my_opts$shiny,"/data/Corpus"))
dir.create(paste0(my_opts$shiny,"/data/models"))
names(corpus)<-gsub(".txt","", names(corpus))
writeCorpus(corpus, paste0(my_opts$shiny,"/data/Corpus"))
load(paste0(my_opts$corpus,"/models/LDA_models_current.rda"))
save(models,file=paste0(my_opts$shiny,"/data/models/LDA_models_current.rda"))
load(paste0(my_opts$corpus,"/models/LDA_FY_models_current.rda"))
save(models.fy,file=paste0(my_opts$shiny,"/data/models/LDA_FY_models_current.rda"))
metaData<-read.csv(paste0(my_opts$corpus,"/CorpusMetaData.txt"),
colClasses=c('character','character','Date','character','character','numeric','integer',
'logical'))
if(file.exists(paste0(my_opts$corpus,"/models/ModelsMetaData.txt"))){
modelMetaData<-read.csv(paste0(my_opts$corpus,"/models/ModelsMetaData.txt"),
colClasses=c('character','character','Date','character',
'character','numeric','integer'))
write.csv(modelMetaData, file=paste0(my_opts$shiny,"/models/modelMetaData.txt"), row.names=F)
} else{
z<-unlist(lapply(names(corpus), function(x) which(metaData$PMID==x)))
modelMetaData<-metaData[z,]
write.csv(modelMetaData,paste0(my_opts$corpus,"/models/modelMetaData.txt"), row.names=F)
write.csv(modelMetaData, file=paste0(my_opts$shiny,"/data/modelMetaData.txt"), row.names=F)
}
dtm<-DocumentTermMatrix(corpus)
term.assoc<-crossprod_simple_triplet_matrix(dtm)/
(sqrt(col_sums(dtm^2) %*% t(col_sums(dtm^2))))
term.assoc<-as.simple_triplet_matrix(term.assoc)
save(term.assoc,file = paste0(my_opts$corpus,"/models/termAssoc.rda"))
save(term.assoc,file = paste0(my_opts$shiny,"/data/models/termAssoc.rda"))
tdm<-TermDocumentMatrix(corpus)
save(tdm, file=paste0(my_opts$corpus,"/Corpus_TDM.rda"))
save(tdm, file=paste0(my_opts$shiny,"/data/Corpus_TDM.rda"))
beta.tree<-lapply(models,
function(x) lapply(c("cosine", "Hellinger", "correlation", "Bhjattacharyya"),
function (z) hclust(dist(exp(x@beta), z))))
save(beta.tree, file = paste0(my_opts$corpus,"/models/beta.tree.rda"))
save(beta.tree, file = paste0(my_opts$shiny,"/data/models/beta.tree.rda"))
###GrantID-PMID co-occurency network
grantIDs<-strsplit(metaData$GrantID, "\\|")
gi<-as.character(unlist(grantIDs))
gi1<-gsub("\\d","0", gi)
gi1<-gsub("[A-Za-z]","A",gi1)
#levels(as.factor(gi1))
gi<-gsub("/|\\\\|:|#|\\.$|\\(|\\)|,", "", gi)
gi<-gsub(paste(ICs,collapse="|"), "",gi)
gi<-gsub("[A-Z]{4,}[\\s|-]","",gi, perl=T)
gi<-gsub("^[^A-Za-z0-9]\\s*","",gi)
gi<-gsub("^-","", gi, perl=T)
gi2<-gsub("\\d", "0",gi)
gi2<-gsub("[A-Za-z]", "A",gi2,perl = T)
#levels(as.factor(gi2))
#summary(as.factor(gi2))
gi3<-gsub(paste0("^[\\d]",paste(activityCodes,collapse="|^")),"", gi, perl=T)
gi3<-gsub("\\s|-|\\.|\\*|_", "",gi3, perl=T)
gi3<-gsub(".*([A-Z]{2}\\d{6}).*", "\\1", gi3, perl=T)
gi4<-gsub("\\d", "0",gi3)
gi4<-gsub("[A-Za-z]", "A",gi4,perl = T)
#levels(as.factor(gi4))
grants.table<-data.frame(PMID=rep(metaData$PMID,sapply(grantIDs, length)),
grantID=gi3,
year=rep(metaData$FY,sapply(grantIDs, length)))
write.table(grants.table, paste0(my_opts$corpus,"/PMIDs_to_grants.txt"),col.names = T,sep="\t",quote=T, row.names=F)
write.table(grants.table, paste0(my_opts$shiny,"/data/PMIDs_to_grants.txt"),col.names = T,sep="\t",quote=T, row.names=F)
##FY model-model distance measures.
betaTreeFY<-list()
betaTreeFY<-lapply(c("cosine","correlation","hellinger"), function(x) {
lapply(3:(length(models.fy)-2), function(i) {
lapply(1:(length(models.fy[[i]])-1), function(j){
dist(models.fy[[i]][[j]]@beta,models.fy[[i+1]][[j]]@beta, method=x)
})
})
})
betaTreeFY_2<-rep(list(rep(list(rep(list(),6)),5)),3)
for (m in seq_along(betaTreeFY)){
for (k in seq_along(betaTreeFY[[1]][[1]])){
for (y in seq_along(betaTreeFY[[1]]))
betaTreeFY_2[[m]][[k]][[y]]<-betaTreeFY[[m]][[y]][[k]]
}
}
names(betaTreeFY_2)<-c("cosine","correlation","hellinger")
fys<-c(2009,2010,2011,2012,2013,2014,2015) ##This should be dynamically set from input data source.
betaTreeEdgeList<-lapply(betaTreeFY_2, function(m){
lapply(m, function(k){
do.call(rbind, lapply(seq_along(k), function(y){
el<-dist2Table(k[[y]])
el$source<-paste0("FY",fys[y],"_Topic",el$source)
el$target<-paste0("FY",fys[y+1],"_Topic",el$target)
el[,"FYsource"]<-fys[y]
el[,"FYtarget"]<-fys[y+1]
el
}))
})
})
save(betaTreeEdgeList, file=paste0(my_opts$shiny,"/models/betaTreeEdgeList.rda"))
topicTerms<-lapply(models.fy, function(y) {
lapply(y, function (k)
apply(terms(k,4), 2, function(z) paste(z, collapse=",")))
})